IoT – Condition Based Monitoring

TAZI’s ML platform enabled reducing the frequency of regular maintenance by predicting failures or anomalies in advance and avoiding unnecessary maintenance costs.

  • Improve management of IoT sensors 
  • Decrease maintenance costs 

IoT – Unsupervised Sensor Compression & Condition Monitoring

Customers want to use sensor data to predict machine failures in advance to reduce costs. TAZI ML algorithms not just helped to predict machine failures beforehand but also provided detection of which sensor data have critical importance.

  • Understand when and how sensors will fail 
  • Prioritize machine maintenance based on sensor data importance

IoT – Edge Condition Monitoring & Predictive Maintenance

In this particular example, medical cabinet lock failure causes customer dissatisfaction and also high maintenance costs. TAZI ML platform is used to predict lock failures in advance so that predictive actions can be taken before the lock failure happens.

  • Decrease the number of lock failures and improve customer satisfaction
  • Understand the root cause of each failure for better manufacturing

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